Engineering Commons^™

Fluid Flow In Micro-Channels: A Stochastic Approach, Hilda Marino Black

Doctoral Dissertations

In this study free molecular flow in a micro-channel was modeled using a stochastic approach, namely the Kolmogorov forward equation in three dimensions. Model equations were discretized using Central Difference and Backward Difference methods and solved using the Jacobi method. Parameters were used that reflect the characteristic geometry of experimental work performed at the Louisiana Tech University Institute for Micromanufacturing.

The solution to the model equations provided the probability density function of the distance traveled by a particle in the micro-channel. From this distribution we obtained the distribution of the residence time of a particle in the micro-channel. Knowledge of …

A Hybrid Finite Element-Finite Difference Method For Thermal Analysis In A Double-Layered Thin Film, Teng Zhu

Doctoral Dissertations

Thin film technology is of vital importance in microtechnology applications. For instance, thin films of metals, of dielectrics such as SiO2, or Si semiconductors are important components of microelectronic devices. The reduction of the device size to the microscale has the advantage of enhancing the switching speed of the device. The reduction, on the other hand, increases the rate of heat generation that leads to a high thermal load on the microdevice. Heat transfer at the microscale with an ultrafast pulsed-laser is also a very important process for thin films. Hence, studying the thermal behavior of thin films or of …

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …