Evolutionary Computation Applied to Urban Traffic Optimization

At the present time, many sings seem to indicate that we live a global energy and environmental crisis. The scientific community argues that the global warming process is, at least in some degree, a consequence of modern societies unsustainable development. A key area in that situation is the citizens mobility. World economies seem to require fast and efficient transportation infrastructures for a significant fraction of the population. The non-stopping overload process that traffic networks are suffering calls for new solutions. In the vast majority of cases it is not viable to extend that infrastructures due to costs, lack of available space, and environmental impacts. Thus, traffic departments all around the world are very interested in optimizing the existing infrastructures to obtain the very best service they can provide. In the last decade many initiatives have been developed to give the traffic network new management facilities for its better exploitation. They are grouped in the so called Intelligent Transportation Systems. Examples of these approaches are the Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS). Most of them provide drivers or traffic engineers the current traffic real/simulated situation or traffic forecasts. They may even suggest actions to improve the traffic flow. To do so, researchers have done a lot of work improving traffic simulations, specially through the development of accurate microscopic simulators. In the last decades the application of that family of simulators was restricted to small test cases due to its high computing requirements. Currently, the availability of cheap faster computers has changed this situation. Some famous microsimulators are MITSIM(Yang, Q., 1997), INTEGRATION (Rakha, H., et al., 1998), AIMSUN2 (Barcelo, J., et al., 1996), TRANSIMS (Nagel, K. & Barrett, C., 1997), etc. They will be briefly explained in the following section. Although traffic research is mainly targeted at obtaining accurate simulations there are few groups focused at the optimization or improvement of traffic in an automatic manner â not dependent on traffic engineers experience and âartâ. O pe n A cc es s D at ab as e w w w .ite ch on lin e. co

Predicting complex system behavior using hybrid modeling and computational intelligence

“Modeling and prediction of complex systems is a challenging problem due to the sub-system interactions and dependencies. This research examines combining various computational intelligence algorithms and modeling techniques to provide insights into these complex processes and allow for better decision making. This hybrid methodology provided additional capabilities to analyze and predict the overall system behavior where a single model cannot be used to understand the complex problem. The systems analyzed here are flooding events and fetal health care. The impact of floods on road infrastructure is investigated using graph theory, agent-based traffic simulation, and Long Short-Term Memory deep learning to predict water level rise from river gauge height. Combined with existing infrastructure models, these techniques provide a 15-minute interval for making closure decisions rather than the current 6-hour interval. The second system explored is fetal monitoring, which is essential to diagnose severe fetal conditions such as acidosis. Support Vector Machine and Random Forest were compared to identify the best model for classification of fetal state. This model provided a more accurate classification than existing research on the CTG. A deep learning forecasting model was developed to predict the future values for fetal heart rate and uterine contractions. The forecasting and classification algorithms are then integrated to evaluate the future condition of the fetus. The final model can predict the fetal state 4 minutes ahead to help the obstetricians to plan necessary interventions for preventing acidosis and asphyxiation. In both cases, time series predictions using hybrid modeling provided superior results to existing methods to predict complex behaviors”--Abstract, page iv

Bridging two worlds: baroque violin performance practices as a model for the transcription of selected movements of J.S. Bach's sonatas and partitas for solo violin on the modern guitar

This document explores the role of the baroque violin practices of bowing, chord playing, and slurring in arrangements for the modern guitar, of selected movements of J. S. Bach’s Sonatas and Partitas (BWV 1001-1006) for solo violin. This document aims to expand the range of possible solutions for all guitarists interested in playing Bach’s unaccompanied solo music by making a “bridge” between these essential performance practices of the baroque violin and the capabilities of the modern guitar. Some practices associated with other baroque instruments such as the lute and the harpsichord are also considered. The guitar arrangements included at the end of the document were conceived taking into account techniques that were intrinsic to Bach’s conception of these violin pieces as violin music. As a consequence, the musical content has a primary position in the final product. The methodology is primarily based on the study of the bowing practices, and the slurring practices of the baroque violin (both of them essential aspects of the technique of the instrument) and their realization in terms of modern classical guitar technique. These elements of violin technique are the structural pillars of the proposed bridge. Secondary to them, the way chords are played on the baroque violin and how it can promote ease of playing and good voice leading in the guitar arrangements is also part of the methodology. The rationale that represents the “bridge” is first presented and then compared to other approaches found in various published editions of Bach’s violin music arranged for the modern guitar

In vitro analyses of Merkel cell polyomavirus cell biology

The work described in this dissertation was initiated in 2008, shortly after the discovery of Merkel cell polyomavirus (MCV). MCV was discovered as clonally integrated in 80% of Merkel cell carcinoma (MCC) and tumor-derived viral genomes were found to harbor individual large T antigen (LT) truncating deletions. The work presented in this thesis focuses on two main features associated with MCV cell biology: (1) Viral replication requirements that promote viral origin replication in the context of full length MCV LT (chapter 3) and (2) cellular targets that enhance human fibroblast proliferation in the presence of tumor-derived full length LT (chapter 4). As part of these studies, the novel MCV-positive MCC cell line MS-1 was generated, and its cellular and viral features are presented here (chapter 2). MCC cell lines are useful tools that can be used to study MCV biology, and test therapeutic compounds in vitro, as well as in a xenograft setting in vivo as described in the appendix of this thesis. Within the past 6 years, 8 new human polyomaviruses have been identified through basic biological approaches, highlighting the possibility that other human malignancies may be associated with polyomaviral infections. The identification of MCV in association with an aggressive human cancer also underscores the relevance of basic research in understanding human disease