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University of Windsor

Electronic Theses and Dissertations

2018

Machine Learning

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Novel Methods For Permanent Magnet Demagnetization Detection In Permanent Magnet Synchronous Machines, Min Zhu Dec 2018

Novel Methods For Permanent Magnet Demagnetization Detection In Permanent Magnet Synchronous Machines, Min Zhu

Electronic Theses and Dissertations

Monitoring and detecting PM flux linkage is important to maintain a stable permanent magnet synchronous motor (PMSM) operation. The key problems that need to be solved at this stage are to: 1) establish a demagnetization magnetic flux model that takes into account the influence of various nonlinear and complex factors to reveal the demagnetization mechanism; 2) explore the relationship between different factors and demagnetizing magnetic field, to detect the demagnetization in the early stage; and 3) propose post-demagnetization measures. This thesis investigates permanent magnet (PM) demagnetization detection for PMSM machines to achieve high-performance and reliable machine drive for practical industrial …


Identification Of User Behavioural Biometrics For Authentication Using Keystroke Dynamics And Machine Learning, Sowndarya Krishnamoorthy Apr 2018

Identification Of User Behavioural Biometrics For Authentication Using Keystroke Dynamics And Machine Learning, Sowndarya Krishnamoorthy

Electronic Theses and Dissertations

This thesis focuses on the effective classification of the behavior of users accessing computing devices to authenticate them. The authentication is based on keystroke dynamics, which captures the users behavioral biometric and applies machine learning concepts to classify them. The users type a strong passcode ”.tie5Roanl” to record their typing pattern. In order to confirm identity, anonymous data from 94 users were collected to carry out the research. Given the raw data, features were extracted from the attributes based on the button pressed and action timestamp events. The support vector machine classifier uses multi-class classification with one vs. one decision …


Acceleration Of K-Nearest Neighbor And Srad Algorithms Using Intel Fpga Sdk For Opencl, Liyuan Liu Mar 2018

Acceleration Of K-Nearest Neighbor And Srad Algorithms Using Intel Fpga Sdk For Opencl, Liyuan Liu

Electronic Theses and Dissertations

Field Programmable Gate Arrays (FPGAs) have been widely used for accelerating machine learning algorithms. However, the high design cost and time for implementing FPGA-based accelerators using traditional HDL-based design methodologies has discouraged users from designing FPGA-based accelerators. In recent years, a new CAD tool called Intel FPGA SDK for OpenCL (IFSO) allowed fast and efficient design of FPGA-based hardware accelerators from high level specification such as OpenCL. Even software engineers with basic hardware design knowledge could design FPGA-based accelerators. In this thesis, IFSO has been used to explore acceleration of k-Nearest-Neighbour (kNN) algorithm and Speckle Reducing Anisotropic Diffusion (SRAD) simulation …


Machine Learning Approaches For Cancer Analysis, Alkhateeb Abedalrhman Jan 2018

Machine Learning Approaches For Cancer Analysis, Alkhateeb Abedalrhman

Electronic Theses and Dissertations

In addition, we propose many machine learning models that serve as contributions to solve a biological problem. First, we present Zseq, a linear time method that identifies the most informative genomic sequences and reduces the number of biased sequences, sequence duplications, and ambiguous nucleotides. Zseq finds the complexity of the sequences by counting the number of unique k-mers in each sequence as its corresponding score and also takes into the account other factors, such as ambiguous nucleotides or high GC-content percentage in k-mers. Based on a z-score threshold, Zseq sweeps through the sequences again and filters those with a z-score …