Optimal Portfolio Using a Genetic Algorithm

Distributing the amount of money to invest in each stock of a portfolio, while maximizing profit and minimizing risk is key. This project applied the method of a genetic algorithm in order to select an optimal portfolio. A genetic algorithm generates solutions to optimization problems using techniques inspired by natural evolution. A five stock, five years’ portfolio was utilized in order to demonstrate the efficiency of a genetic algorithm. The most important steps of this method were the fitness function and the crossover. The fitness function is a formula that determined the effectiveness of the portfolio distribution; it returned a value for each portfolio distribution and the higher the value the better the distribution. The fitness function allowed us to rank and sort the generated distributions. Then, the crossover was performed in order to see how the genetic algorithm converges towards the optimal solution. The best portfolio distributions, according to the fitness function, were used for the crossover in order to generate even better distributions. Crossover was executed a couple of times by generating new generations of distributions, until the best distribution was produced. The best distribution produced a twenty-five percent average return and its computing time was eleven minutes

Study of the Stability of Heparin/Collagen Layer-By-Layer Coatings

Pairing heparin with collagen-based medical implants has opened a whole new area of research for enhancing the desired effect of current implants. In fact, heparin (HEP) and collagen (COL) layer-by-layer (LbL) coatings have shown impressive results in forming polyelectrolyte multilayers. It has been already seen on skin grafts, nerve guide conduits (NGCs), and drug delivery devices yielding promising results. Due to being a simple, cost-efficient, and versatile option to fabricate thin biomimetic films, this self-assembly technique is one of the most effective methods to immobilize extracellular matrix (collagen and heparin) onto medical devices and implants. Even though previous studies have shown that HEP/COL coatings improve cell adhesion, migration, proliferation, and expansion of human Schwann cells (hSCs), the stability of these polymer coatings over time remains uncertain. Schwann cells are neuronal glial cells essential for maintaining the integrity, growth, and – important to our research - the regeneration of nervous tissue. This research focused on studying the stability of six bilayers of HEP/COL LbL coatings, which will be noticed as (HEP/COL)6, when incubated in PBS (Phosphate Buffered Saline) and cell culture media. That is, how the (HEP/COL)6 coatings degrade over a certain period and how cell behavior may be affected by the degradation level. The experiments monitored cell behavior in pre-treated coatings in real time and with a PrestoBlue viability assay. It was found that although the cell culture media treatment of the coatings initially offered better conditions to enhance cell behavior, it also rapidly deteriorated the coatings. Furthermore, it was observed that (HEP/COL)6 favors the cell behavior even over three weeks

Study of the Stability of Heparin/Collagen Layer-By-Layer Coatings

Pairing heparin with collagen-based medical implants has opened a whole new area of research for enhancing the desired effect of current implants. In fact, heparin (HEP) and collagen (COL) layer-by-layer (LbL) coatings have shown impressive results in forming polyelectrolyte multilayers. It has been already seen on skin grafts, nerve guide conduits (NGCs), and drug delivery devices yielding promising results. Due to being a simple, cost-efficient, and versatile option to fabricate thin biomimetic films, this self-assembly technique is one of the most effective methods to immobilize extracellular matrix (collagen and heparin) onto medical devices and implants. Even though previous studies have shown that HEP/COL coatings improve cell adhesion, migration, proliferation, and expansion of human Schwann cells (hSCs), the stability of these polymer coatings over time remains uncertain. Schwann cells are neuronal glial cells essential for maintaining the integrity, growth, and – important to our research - the regeneration of nervous tissue. This research focused on studying the stability of six bilayers of HEP/COL LbL coatings, which will be noticed as (HEP/COL)6, when incubated in PBS (Phosphate Buffered Saline) and cell culture media. That is, how the (HEP/COL)6 coatings degrade over a certain period and how cell behavior may be affected by the degradation level. The experiments monitored cell behavior in pre-treated coatings in real time and with a PrestoBlue viability assay. It was found that although the cell culture media treatment of the coatings initially offered better conditions to enhance cell behavior, it also rapidly deteriorated the coatings. Furthermore, it was observed that (HEP/COL)6 favors the cell behavior even over three weeks

Bayesian Modeling For Dealing With Uncertainty In Cognitive Radios

Wireless communication systems can be affected by several factors, including propagation losses, co-channel interference, and multipath fading. Uncertainty affects all of these factors making it even more difficult to model these systems. This dissertation proposes the use of probabilistic graphical models (PGM), such as Bayesian Networks and Influence Diagrams, as the core for reasoning and decision making in adaptive radios operating under uncertainty. PGM constitute a tool to understand and model complex relations among random variables. This dissertation explains how to build effective communication models that perform its functions under uncertainty. In addition, this work also presents a spectrum sensing technique based on the autocorrelation of samples to estimate the utilization level of wireless channels