Diagnosis of MRSA with neural networks and logistic regression approach

Antibiotic-resistant pathogens are increasingly prevalent in the hospitals and community. A timely and accurate diagnosis of the infection would greatly help physicians effectively treat patients. In this research we investigate the potential of using neural networks (NN) and logistic regression (LR) approach in diagnosing methicillin-resistant Staphylococcus aureus (MRSA). Receiver-Operating Characteristic (ROC) curve and the cross-validation method are used to compare the performances of both systems. We found that NN is better than the logistic regression approach, in terms of both the discriminatory power and the robustness. With modeling flexibility inherent in its techniques, NN is effective in dealing with MRSA and other classification problems involving large numbers of variables and interaction complexity. On the other hand, logistic regression in our case is slightly inferior, offers more clarity and less perplexity. It could be a method of choice when fewer variables are involved and/or justification of the results is desired. Copyright Kluwer Academic Publishers 2000

Adaptive Kinetic Architecture and Collective Behavior: A Dynamic Analysis for Emergency Evacuation

Adaptive kinetic architecture has emerged from a need for innovative designs that adapt to the environment and changing needs of the occupants. Architectural design and modes of egress are critical in an emergency. Flocking describes a certain collective behavior where agents are brought together in groups and move as a cohesive unit from place to place. Collective behavior may be observed in microscopic as well as macroscopic environments. Crowd modeling incorporates the study of human behavior, mathematical modeling, and molecular or fluid dynamics. The simulation of agents and their movement in the built environment is beneficial for design professionals, scientists, and engineers. Human behavior in panic situations is notably similar to fluids and molecules. The objective of this research was to evaluate the movement of agents in buildings using discrete dynamic simulation. We used a novel discrete molecular dynamics technique to simulate the evacuation of agents in panic situations. Various adaptive geometric configurations were analyzed for improved crowd flow. Kinetic walls were modeled in order to evaluate design optimization as it relates to rates of egression. This research proposes the use of kinetic walls to improve safety and efficiency during an emergency evacuation. Adaptive geometric configurations show improvements over the conventional design framework