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Full-Text Articles in Engineering
Application Of Polyelectrolyte Layer-By-Layer Nano-Assembly For Surface Modification, Encapsulation And Controlled Release, Nikhil Anil Pargaonkar
Application Of Polyelectrolyte Layer-By-Layer Nano-Assembly For Surface Modification, Encapsulation And Controlled Release, Nikhil Anil Pargaonkar
Doctoral Dissertations
In this study, we applied the traditional Electrostatic layer-by-layer (ELBL) assembly procedure to fabricate nanothin films over flat surfaces, and modify particle surfaces to influence the drug particle size, and drug release. The ELBL assembly has previously been applied to fabricate multilayer nano-scale thin films, but its ability to instantaneously influencing particle size is unique. Other unique observations such as influence on drug release as a result of polymer complexation, and thermal changes occurring during layer fabrication are recorded.
The ELBL self-assembly process was applied to produce dexamethasone particles layered with various polyelectrolyte layer combinations. These combinations were further applied …
Effects Of Diabetes And Aging On Posture And Acceleration Thresholds During Lateral Translations, Samantha Jean Richerson
Effects Of Diabetes And Aging On Posture And Acceleration Thresholds During Lateral Translations, Samantha Jean Richerson
Doctoral Dissertations
Research objectives. One source of falls in the elderly may be an inability to sufficiently adjust to transient postural perturbations or slips. Identifying useful predictors of fall potential, as well as factors that affect the ability of an individual to detect a movement of the standing support surface may provide insight into postural stability and methods to increase stability in elders. To do this, acceleration thresholds to short, precise, lateral platform translations and the resultant psychophysical responses of adults with early Type 2 diabetes to age-matched controls and young adults were measured.
Methods. Using an innovative SLIP-FALLS platform, …
Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94
Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94
Doctoral Dissertations
The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.
Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …