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You searched for +publisher:"Cornell University" +contributor:("Delchamps, David Forbes"). Showing records 1 – 3 of 3 total matches.

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Cornell University

1. Marvel, Seth. Simple Mathematical Models Of Social Behavior.

Degree: PhD, Applied Mathematics, 2011, Cornell University

We present and analyze minimal models for three social phenomena: the development of two-sided conflicts, interactions between conformists and contrarians, and pair formation between individuals seeking mates. In all three cases, the phenomena can be viewed as processes occurring on the node or edge values of a graph with fixed topology. Together, these three case studies illustrate that mathematical analysis of simple models may give us mechanistic insight into how real social systems behave. Advisors/Committee Members: Strogatz, Steven H (chair), Delchamps, David Forbes (committee member), Kleinberg, Jon M (committee member).

Subjects/Keywords: social dynamics; structural balance; coupled oscillators

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APA (6th Edition):

Marvel, S. (2011). Simple Mathematical Models Of Social Behavior. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/29478

Chicago Manual of Style (16th Edition):

Marvel, Seth. “Simple Mathematical Models Of Social Behavior.” 2011. Doctoral Dissertation, Cornell University. Accessed September 25, 2020. http://hdl.handle.net/1813/29478.

MLA Handbook (7th Edition):

Marvel, Seth. “Simple Mathematical Models Of Social Behavior.” 2011. Web. 25 Sep 2020.

Vancouver:

Marvel S. Simple Mathematical Models Of Social Behavior. [Internet] [Doctoral dissertation]. Cornell University; 2011. [cited 2020 Sep 25]. Available from: http://hdl.handle.net/1813/29478.

Council of Science Editors:

Marvel S. Simple Mathematical Models Of Social Behavior. [Doctoral Dissertation]. Cornell University; 2011. Available from: http://hdl.handle.net/1813/29478


Cornell University

2. Wong, Bernard. Efficient Location-Aware Node And Object Discovery In Large-Scale Networks.

Degree: PhD, Computer Science, 2011, Cornell University

The performance of many distributed systems is highly sensitive to the latency of finding objects in response to user requests. Efficient discovery of nodes and objects in the network that satisfy application-specific requirements is therefore a critical building block for many distributed systems. In this thesis, I introduce a space-based approach to solving node and object discovery problems. This approach represents the relationship between nodes and objects as distances in an abstract space, maps optimization objectives and constraints of the problem to regions in the space, and combines these regions to identify the solution to the discovery problem. Using the space-based approach, I address three common problems involving node and object discovery. First, I tackle the problem of efficiently discovering nodes with specific network latency characteristics, such as finding the closest server node to a target. This problem is commonly encountered in content distribution networks, online games, and other network services that demand low latency. I describe a system, called Meridian, that uses overlay routing in a small-world inspired network to solve such problems efficiently and accurately. Second, I address the decentralized approximate search problem, where the objective is to efficiently scan an online database for the set of objects that are most similar to given search terms. I describe the Cubit system, which provides a fully decentralized and efficient approximate search primitive for peer-to-peer systems. Finally, I solve the problem of accurately determining the physical location of Internet hosts and describe the Octant system, which uses a novel geometric technique to determine a target node's location from constraints extracted from network measurements. I characterize the performance and accuracy of these systems with data and evaluations drawn from deployments on PlanetLab and end-user systems. The results show that these space-based systems are accurate, efficient and scalable. Advisors/Committee Members: Sirer, Emin G. (chair), Delchamps, David Forbes (committee member), Tardos, Eva (committee member).

Subjects/Keywords: Distributed systems; Networking; Localization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wong, B. (2011). Efficient Location-Aware Node And Object Discovery In Large-Scale Networks. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/30619

Chicago Manual of Style (16th Edition):

Wong, Bernard. “Efficient Location-Aware Node And Object Discovery In Large-Scale Networks.” 2011. Doctoral Dissertation, Cornell University. Accessed September 25, 2020. http://hdl.handle.net/1813/30619.

MLA Handbook (7th Edition):

Wong, Bernard. “Efficient Location-Aware Node And Object Discovery In Large-Scale Networks.” 2011. Web. 25 Sep 2020.

Vancouver:

Wong B. Efficient Location-Aware Node And Object Discovery In Large-Scale Networks. [Internet] [Doctoral dissertation]. Cornell University; 2011. [cited 2020 Sep 25]. Available from: http://hdl.handle.net/1813/30619.

Council of Science Editors:

Wong B. Efficient Location-Aware Node And Object Discovery In Large-Scale Networks. [Doctoral Dissertation]. Cornell University; 2011. Available from: http://hdl.handle.net/1813/30619


Cornell University

3. Wang, Xiaozhe. Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods.

Degree: PhD, Electrical Engineering, 2015, Cornell University

Due to the growing load demand and aging transmission networks, many power systems have been pushed ever closer to their stability limits. Furthermore, the increasing penetration of renewable energies and rapid development of the smart grids result in more stability concerns beyond the short-term time scale. All above factors highlight the significance to study the long-term stability analysis of power systems. This dissertation contributes to the long-term stability analysis of traditional power systems as well as the power grids with wind power by providing nonlinear analysis, establishing theoretical foundations, developing computational tools and implementing new numerical methods. The quasi steady-state (QSS) model was regarded as a competent model to provide accurate stability analysis with fast speed in long-term stability analysis. Our study, however, has shown that the QSS model may provide incorrect (over-optimistic) stability assessment. Hence, in this dissertation, limitations of the QSS model are comprehensively analyzed in a nonlinear system framework. A theoretical foundation for the QSS model is developed, which provides sufficient conditions under which the QSS model can provide accurate approximations for the long-term stability model in terms of trajectories and [omega]-limit set. Furthermore, two hybrid QSS models are proposed from the physical and the- oretical perspectives respectively, which are remedies to the QSS model. Each hybrid QSS model is provided with efficient numerical schemes for practical implementation, and the generic hybrid QSS model is also equipped with a theoretical basis to ensure consistently accurate approximations for the long-term stability model. Apart from the model development in long-term stability analysis, this dissertation also provides some numerical development. A theory-based numerical method, pseudo transient-continuation method, is improved and applied in long-term stability research to expedite simulation speed in the long-term stability model and overcome numerical difficulties in the QSS model. The work provides an alternative numerical method to the conventional integration methods in time domain simulation with good efficiency and stability properties. In addition, this dissertation involves long-term stability analysis of the power systems integrating wind power. A stochastic formulation of power system models incorporating wind power is presented based on stochastic differential equations, and a novel methodology to conduct stability analysis for these systems is developed with a theoretical foundation. The work may represent the first attempt to exploit the singular perturbation method for SDE in power system stability research. Advisors/Committee Members: Chiang, Hsiao-Dong (chair), Delchamps, David Forbes (committee member), Rand, Richard Herbert (committee member).

Subjects/Keywords: power system dynamics; power system stability; renewable energies

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, X. (2015). Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/39433

Chicago Manual of Style (16th Edition):

Wang, Xiaozhe. “Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods.” 2015. Doctoral Dissertation, Cornell University. Accessed September 25, 2020. http://hdl.handle.net/1813/39433.

MLA Handbook (7th Edition):

Wang, Xiaozhe. “Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods.” 2015. Web. 25 Sep 2020.

Vancouver:

Wang X. Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods. [Internet] [Doctoral dissertation]. Cornell University; 2015. [cited 2020 Sep 25]. Available from: http://hdl.handle.net/1813/39433.

Council of Science Editors:

Wang X. Study Of Long-Term Stability Analysis Of Power Systems With Renewable Energy: Theory, Modeling And Numerical Methods. [Doctoral Dissertation]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/39433

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