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Electronic protoyping is becoming a part of every scientific inquiry and product design, and is the focus of research in the new scientific field of Computational Science and Engineering. The new grand challenge here is the rapid prototyping of manufactured artifacts and the rapid solution to...
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Purpose – Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach – The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents...
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We introduce three new mechanisms that allow trust to be built into cloud computing called the Private Virtual Infrastructure (PVI), the Locator Bot (LoBot), and the Trusted Virtual Environment Module (TVEM). Cloud computing requires that organizations trust that a service provider’s platforms...
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A credit derivative is a financial instrument whose value depends on the credit risk of an underlying asset or assets. Credit risk is the possibility that the obligor fails to honor any payment obligation. This thesis proposes four new computational methods for the valuation of credit...
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With the emergence of the Internet as a global structure for communication and interaction,many “business to consumer” and “business to business” applications have migrated online,thus increasing the need for software agents that can act on behalf of people, institutions orcompanies with...
Persistent link: https://www.econbiz.de/10009455276
This thesis develops a generic framework based on the Fourier transform for pricing and hedging of various options in equity, commodity, currency, and insurance markets. The pricing problem can be reduced to solving a partial integro-differential equation (PIDE). The Fourier Space Time-stepping...
Persistent link: https://www.econbiz.de/10009455281
One desirable property of machine learning algorithms is the ability to balance the number of parameters in a model in accordance with the amount of available data.Incorporating nonparametric Bayesian priors into models is one approach of automatically adjusting model capacity to the amount of...
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