Design and Analysis of Vehicle Sharing Programs: A Systems Approach

Transit, touted as a solution to urban mobility problems, cannot match the addictive flexibility of the automobile. 86% of all trips in the U.S. are in personal vehicles. A more recent approach to reduce automobile dependence is through the use of Vehicle Sharing Programs (VSPs). A VSP involves a fleet of vehicles located strategically at stations across the transportation network. In its most flexible form, users are free to check out vehicles at any station and return the vehicle at a station close to their destination. Vehicle fleets are comprised of bicycles, cars or electric vehicles. Such systems offer innovative solutions to the larger mobility problem and can have positive impacts on the transportation system as a whole by reducing urban congestion. This dissertation employs a network modeling framework to quantitatively design and operate VSPs. At the strategic level, the problem of determining the optimal VSP configuration is studied. A bilevel optimization model and associated solution methods are developed and implemented for a large-scale case study in Washington D.C. The model explicitly considers the intermodalism, and views the VSP as a `last-mile' connection of an existing transit network. At the operational level, by transferring control of vehicles to the user for improved system flexibility, exceptional logistical challenges are placed on operators who must ensure adequate vehicle stock (and parking slots) at each station to service all demand. Since demand in the short-term can be asymmetric (flow from one station to another is seldom equal to flow in the opposing direction), service providers need to redistribute vehicles to correct this imbalance. A chance-constrained program is developed that generates least-cost redistribution plans such that most demand in the near future is met. Since the program has a non-convex feasible region, two methods for its solution are developed. The model is applied to a real-world car-sharing system in Singapore where the value of accounting for inherent stochasticities is demonstrated. The framework is used to characterize the efficiency of Velib, a large-scale bicycle sharing system in Paris, France

Co-creating a globally interpretable model with human input

We consider an aggregated human-AI collaboration aimed at generating a joint interpretable model. The model takes the form of Boolean decision rules, where human input is provided in the form of logical conditions or as partial templates. This focus on the combined construction of a model offers a different perspective on joint decision making. Previous efforts have typically focused on aggregating outcomes rather than decisions logic. We demonstrate the proposed approach through two examples and highlight the usefulness and challenges of the approach.Comment: Paper at Artificial Intelligence & Human-Computer Interaction Workshop at ICML 202

Cysteine Desulfurase And Isd11: A Drosophila Model

ABSTRACT Cysteine desulfurase and Isd11: A Drosophila model Iron-sulfur clusters are cofactors with evolutionary origins that date back to the pre-biotic world. Ever since life originated, these cofactors have intermingled with proteins to play vital roles in sustaining life. My research focuses on one such protein, the cysteine desulfurase (Nfs) that has the PLP cofactor incorporated in its active site and avails of the catalytic property of PLP to provide sulphur for Iron-sulfur cluster biogenesis and assembly in a cell. Interestingly, in a eukaryotic cell, despite the versatility of PLP, cysteine desulfurase\u27s role as a sulphur-extractor is incomplete without another protein named Isd11. This interesting piece of evidence led us to perform basic protein characterisation of both the proteins so as to biophysically study the binding event and conformational changes during persulfide formation in future. We chose Drosophila as our model organism. We have been able to successfully create a working model for further characterisation of the binding event during persulfide formation and also, study the complexation event involving all Iron-sulfur cluster biogenesis assembly proteins during 2Fe-2S cluster formation

Analogy-Based Assessment of Domain-Specific Word Embeddings

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