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Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013., Cataloged from PDF version of thesis., Includes bibliographical references (pages 99-101)., One of the main challenges of making strategic decisions in transportation is that we always face a set of possible future states due to deep uncertainty in traffic demand. This thesis focuses on exploring the application of model-based decision support techniques which characterize a set of future states that represent the vulnerabilities of the proposed policy. Vulnerabilities here are interpreted as states of the world where the proposed policy fails its performance goal or deviates significantly from the optimum policy due to deep uncertainty in the future. Based on existing literature and data mining techniques, a computational model-based approach known as scenario discovery is described and applied in an empirical problem. We investigated the application of this new approach in a case study based on a proposed transit policy implemented in Marina Bay district of Singapore. Our results showed that the scenario discovery approach performs well in finding the combinations of uncertain input variables that will result in policy failure., by Xiang Song., S.M.in Transportation

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013., Cataloged from PDF version of thesis., Includes bibliographical references (pages 99-101)., One of the main challenges of making strategic decisions in transportation is that we always face a set of possible future states due to deep uncertainty in traffic demand. This thesis focuses on exploring the application of model-based decision support techniques which characterize a set of future states that represent the vulnerabilities of the proposed policy. Vulnerabilities here are interpreted as states of the world where the proposed policy fails its performance goal or deviates significantly from the optimum policy due to deep uncertainty in the future. Based on existing literature and data mining techniques, a computational model-based approach known as scenario discovery is described and applied in an empirical problem. We investigated the application of this new approach in a case study based on a proposed transit policy implemented in Marina Bay district of Singapore. Our results showed that the scenario discovery approach performs well in finding the combinations of uncertain input variables that will result in policy failure., by Xiang Song., S.M.in Transportation

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013., Cataloged from PDF version of thesis., Includes bibliographical references (pages 99-101)., One of the main challenges of making strategic decisions in transportation is that we always face a set of possible future states due to deep uncertainty in traffic demand. This thesis focuses on exploring the application of model-based decision support techniques which characterize a set of future states that represent the vulnerabilities of the proposed policy. Vulnerabilities here are interpreted as states of the world where the proposed policy fails its performance goal or deviates significantly from the optimum policy due to deep uncertainty in the future. Based on existing literature and data mining techniques, a computational model-based approach known as scenario discovery is described and applied in an empirical problem. We investigated the application of this new approach in a case study based on a proposed transit policy implemented in Marina Bay district of Singapore. Our results showed that the scenario discovery approach performs well in finding the combinations of uncertain input variables that will result in policy failure., by Xiang Song., S.M.in Transportation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2007., Vita., Includes bibliographical references., In this thesis, I study several problems in the following areas: collective excitations in condensed matter physics, noise in gene network and stochastic control in biophysics. In the first area, I construct an effective field theory to describe Bose-Einstein Condensate (BEC) realized in an external potential. This theory explicitly explores the idea of spontaneous symmetry breaking and its application in the description of phase transitions of confined systems. Based on the effective lagrangian, I calculate the excitation spectrum and Matsubara Green's functions using the method of functional integrals. The theory also shows that in one dimension the collective excitation of a bosonic system can be unified with that of a fermionic system, which is described by Luttinger liquid theory. The unified theory of collective excitations of low dimensional quantum systems motivates my study of collective excitations of interacting classical particles confined in one dimension. It is shown in my paper that the structure of Hamiltonian or Lagrangian for one dimensional constrained systems is uniquely determined by conservation laws. Therefore the excitations of bosonic, fermionic and classical particles are strikingly similar in one dimension., (cont.) In the second area, i. e., noise in gene networks and phenotypic switching in a fluctuating environment, I study the noise propagation in a gene network cascade using the method of master equations which examines the validity of the more popular methods such as the Langevin equation. To further explore the applications of stochastic processes for complex systems, I study phenotypic switches in a fluctuating environment. By combining the techniques of stochastic differential equation and stochastic dynamical programming, I propose a simple framework which can be used to study phenotypic growth dynamics. Another work is to explore the influence of environment on the dynamical properties of small systems is directed to the unusual blinking statistics of semiconductor quantum dots. I show in a model system that a broad spectrum of decay rates is possible when disorder is present in the environment., by Xiang Xia., Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2007., Vita., Includes bibliographical references., In this thesis, I study several problems in the following areas: collective excitations in condensed matter physics, noise in gene network and stochastic control in biophysics. In the first area, I construct an effective field theory to describe Bose-Einstein Condensate (BEC) realized in an external potential. This theory explicitly explores the idea of spontaneous symmetry breaking and its application in the description of phase transitions of confined systems. Based on the effective lagrangian, I calculate the excitation spectrum and Matsubara Green's functions using the method of functional integrals. The theory also shows that in one dimension the collective excitation of a bosonic system can be unified with that of a fermionic system, which is described by Luttinger liquid theory. The unified theory of collective excitations of low dimensional quantum systems motivates my study of collective excitations of interacting classical particles confined in one dimension. It is shown in my paper that the structure of Hamiltonian or Lagrangian for one dimensional constrained systems is uniquely determined by conservation laws. Therefore the excitations of bosonic, fermionic and classical particles are strikingly similar in one dimension., (cont.) In the second area, i. e., noise in gene networks and phenotypic switching in a fluctuating environment, I study the noise propagation in a gene network cascade using the method of master equations which examines the validity of the more popular methods such as the Langevin equation. To further explore the applications of stochastic processes for complex systems, I study phenotypic switches in a fluctuating environment. By combining the techniques of stochastic differential equation and stochastic dynamical programming, I propose a simple framework which can be used to study phenotypic growth dynamics. Another work is to explore the influence of environment on the dynamical properties of small systems is directed to the unusual blinking statistics of semiconductor quantum dots. I show in a model system that a broad spectrum of decay rates is possible when disorder is present in the environment., by Xiang Xia., Ph.D.