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Full-Text Articles in Physical Sciences and Mathematics
Robust Sensor Design For The Novel Reduced Models Of The Mead-Marcus Sandwich Beam Equation, Ahmet Aydin
Robust Sensor Design For The Novel Reduced Models Of The Mead-Marcus Sandwich Beam Equation, Ahmet Aydin
Masters Theses & Specialist Projects
Novel space-discretized Finite Differences-based model reductions are proposed for the partial differential equations (PDE) model of a multi-layer Mead-Marcus-type beam with (i) hinged-hinged and (ii) clamped-free boundary conditions. The PDE model describes transverse vibrations for a sandwich beam whose alternating outer elastic layers constrain viscoelastic core layers, which allow transverse shear. The major goal of this project is to design a single boundary sensor, placed at the tip of the beam, to control the overall dynamics on the beam.
For (i), it is first shown that the PDE model is exactly observable by the so-called nonharmonic Fourier series approach. However, …
K-Means Clustering Using Gravity Distance, Ajinkya Vishwas Indulkar
K-Means Clustering Using Gravity Distance, Ajinkya Vishwas Indulkar
Masters Theses & Specialist Projects
Clustering is an important topic in data modeling. K-means Clustering is a well-known partitional clustering algorithm, where a dataset is separated into groups sharing similar properties. Clustering an unbalanced dataset is a challenging problem in data modeling, where some group has a much larger number of data points than others. When a K-means clustering algorithm with Euclidean distance is applied to such data, the algorithm fails to form good clusters. The standard K-means tends to split data into smaller clusters during a clustering process evenly.
We propose a new K-means clustering algorithm to overcome the disadvantage by introducing a different …