The Self-Supervising Machine

Fabric Wrinkle Characterization and Classification Using Modified Wavelet Coefficients and Support-Vector-Machine Classifiers APPROVED BY SUPERVISING COMMITTEE:

Ischemia detection with a self-organizing map supplemented by supervised learning

The problem of maximizing the performance of the detection of ischemia episodes is a difficult pattern classification problem. The motivation for developing the supervising network self-organizing map (sNet-SOM) model is to exploit this fact for designing computationally effective solutions both for the particular ischemic detection problem and for other applications that share similar characte...

Statistical Learning for Multimedia Information Retrieval and Their Applications Approved by Supervising

Application to Adaptive Control to Synchronous Machine Excitation

Self-tuning adaptive control technique has the advantage of being able to track the system operating conditions so that satisfactory control action can always be produced. Self-tuning algorithms can be implemented easily. Because the power systems are usually time varying non-linear systems and their parameters vary, adaptive controllers are very suitable for power systems. Characteristics of a...

Learning Pulse: Using Wearable Biosensors and Learning Analytics to Investigate and Predict Learning Success in Self-regulated Learning

The Learning Pulse study aims to explore whether physiological data such as heart rate and step count correlate with learning activity data and whether they are good predictors for learning success during self-regulated learning. To verify this hypothesis an experiment was set up involving eight doctoral students at the Open University of the Netherlands. Through wearable sensors, heart rate an...